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Machine Learning Predictive Model and Clinical Validation of Nutritional Support Efficacy in Colorectal Malignancies Based on Gut Microbiota Characteristics Construction of a Machine Learning Predictive Model for Nutritional Support Efficacy in Colorectal Malignancies Based on Gut Microbiota Characteristics and Clinical Validation

Machine Learning Predictive Model and Clinical Validation of Nutritional Support Efficacy in Colorectal Malignancies Based on Gut Microbiota Characteristics Construction of a Machine Learning Predictive Model for Nutritional Support Efficacy in Colorectal Malignancies Based on Gut Microbiota Characteristics and Clinical Validation

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500113150
Enrollment
Unknown
Registered
2025-11-25
Start date
2026-01-01
Completion date
Unknown
Last updated
2025-12-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Colorectal Cancer?Malnutrition

Interventions

Observation group:none

Sponsors

The First Affiliated Hospital of Ningbo University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients diagnosed with colorectal malignant tumors in the perioperative period; 2. Aged 18-80 years; 3. Receive standard nutritional support for >=2 weeks (enteral/parenteral nutrition).

Exclusion criteria

Exclusion criteria: 1. Combined with metastasis from tumors outside the digestive tract; 2. Combined with chronic diarrhea, inflammatory bowel disease, and other conditions; 3. Insufficient duration of nutritional support or more than 20% of patient data missing.

Design outcomes

Primary

MeasureTime frame
Effect of nutritional support;—

Countries

China

Contacts

Public ContactWang Jie

The First Affiliated Hospital of Ningbo University

398188506@qq.com+86 574 87089856

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026